Adaboost: Function that implement the algorithm of Ensemble learning in...
In StevenBoys/Ensemblelearn: Use Ensemble learning to better prediction.

Description Usage Arguments Value Examples

Function that implement the algorithm of Ensemble learning in AdaBoost

1	Adaboost(fweak, data, model_num)

`fweak`	- function that generates estimate from weak model based on input
`data`	- list of data that fweak need including x, y and last_est
`model_num`	- the number of weak models you want to train and combine

A list of

`fitted_value`	- fitted value on the training dataset based on the trained model
`model_train`	- a list of trained weak models

fweak <- function(x, y, last_est){
  lm(y ~ -1 + x, weights = last_est)$coefficients
}
data <- list(x = matrix(rnorm(1000), 200, 5))
data$y <- data$x %*% rnorm(5) + rnorm(200, 0, 3)
data$last_est <- rep(1/length(data$y), length(data$y))
model_num <- 100
Adaboost(fweak, data, model_num)